Asymptotic behavior for S-estimators in random design linear model with long-range-dependent errors

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Asymptotic behavior for S-estimators in random design linear model with long-range-dependent errors. / Lin, Zhengyan; Li, Degui; Chen, Jia.

In: Metrika, Vol. 66, No. 3, 11.2007, p. 289-303.

Research output: Contribution to journalArticlepeer-review

Harvard

Lin, Z, Li, D & Chen, J 2007, 'Asymptotic behavior for S-estimators in random design linear model with long-range-dependent errors', Metrika, vol. 66, no. 3, pp. 289-303. https://doi.org/10.1007/s00184-006-0111-6

APA

Lin, Z., Li, D., & Chen, J. (2007). Asymptotic behavior for S-estimators in random design linear model with long-range-dependent errors. Metrika, 66(3), 289-303. https://doi.org/10.1007/s00184-006-0111-6

Vancouver

Lin Z, Li D, Chen J. Asymptotic behavior for S-estimators in random design linear model with long-range-dependent errors. Metrika. 2007 Nov;66(3):289-303. https://doi.org/10.1007/s00184-006-0111-6

Author

Lin, Zhengyan ; Li, Degui ; Chen, Jia. / Asymptotic behavior for S-estimators in random design linear model with long-range-dependent errors. In: Metrika. 2007 ; Vol. 66, No. 3. pp. 289-303.

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@article{aef5cc78a2f14850b2d95066365faf84,
title = "Asymptotic behavior for S-estimators in random design linear model with long-range-dependent errors",
abstract = "The asymptotic behavior of S-estimators in a random design linear model with long-range-dependent Gaussian errors is considered. It turns out that the S-estimators of regression parameter and error variance are strongly consistent under mild conditions. Furthermore, the asymptotic distribution of the S-estimator of regression parameter is normal if the design vectors are i.i.d. and is non-normal if the design vectors are long-range dependent Gaussian vectors. We also show that the asymptotic distribution of S-estimator of the error variance is non-normal since the errors are long-range dependent.",
keywords = "long-range dependence, CONVERGENCE, S-estimator, consistency, linear model, asymptotic distribution, REGRESSION MODEL",
author = "Zhengyan Lin and Degui Li and Jia Chen",
year = "2007",
month = nov,
doi = "10.1007/s00184-006-0111-6",
language = "English",
volume = "66",
pages = "289--303",
journal = "Metrika",
issn = "0026-1335",
publisher = "Springer Verlag",
number = "3",

}

RIS (suitable for import to EndNote) - Download

TY - JOUR

T1 - Asymptotic behavior for S-estimators in random design linear model with long-range-dependent errors

AU - Lin, Zhengyan

AU - Li, Degui

AU - Chen, Jia

PY - 2007/11

Y1 - 2007/11

N2 - The asymptotic behavior of S-estimators in a random design linear model with long-range-dependent Gaussian errors is considered. It turns out that the S-estimators of regression parameter and error variance are strongly consistent under mild conditions. Furthermore, the asymptotic distribution of the S-estimator of regression parameter is normal if the design vectors are i.i.d. and is non-normal if the design vectors are long-range dependent Gaussian vectors. We also show that the asymptotic distribution of S-estimator of the error variance is non-normal since the errors are long-range dependent.

AB - The asymptotic behavior of S-estimators in a random design linear model with long-range-dependent Gaussian errors is considered. It turns out that the S-estimators of regression parameter and error variance are strongly consistent under mild conditions. Furthermore, the asymptotic distribution of the S-estimator of regression parameter is normal if the design vectors are i.i.d. and is non-normal if the design vectors are long-range dependent Gaussian vectors. We also show that the asymptotic distribution of S-estimator of the error variance is non-normal since the errors are long-range dependent.

KW - long-range dependence

KW - CONVERGENCE

KW - S-estimator

KW - consistency

KW - linear model

KW - asymptotic distribution

KW - REGRESSION MODEL

U2 - 10.1007/s00184-006-0111-6

DO - 10.1007/s00184-006-0111-6

M3 - Article

VL - 66

SP - 289

EP - 303

JO - Metrika

JF - Metrika

SN - 0026-1335

IS - 3

ER -